Within business organizations, educational institutions, and other large entities, individual computers are increasingly connected to each other by means of a network. As the number of computers on a network increases, the complex task of managing the networked computers quickly overwhelms information technology departments and service providers. Often, data and processing are dispersed over a heterogeneous network comprising a variety of distinct, interconnected and geographically remote computers.
Among the reasons for this approach are to offload non-mission-critical processing from the mainframe, to provide a pragmatic alternative to centralized corporate databases, to establish a single computing environment, to move control into the operating divisions of the company, and to avoid having a single point of failure. For example, many business entities have one client/server network installed in each regional office, in which a high-capacity computer system operates as the server supporting many lower-capacity client desktop computers. The servers in such a business entity are also commonly connected to one another by a higher-level network known as a wide area network. In this manner, users at any location within the business entity can theoretically access resources available anywhere in the company's network regardless of the location of the resource.
Alternatively, many businesses use a peer-to-peer (“P2P”) network computing approach. A peer-to-peer network is essentially the same as a client/server network with all clients and no servers. However, peer-to-peer networks have a variety of unique qualities which distinguish them from conventional client/server networks. In a peer-to-peer network, for example, the network composition can change dynamically and continuously, as peers join and leave the network. Consequently, it is frequently necessary for applications running on individual computers to determine the presence or absence of a particular machine before attempting to communicate with said machine. Peer-to-peer networks are usually decentralized and allow for the spontaneous, continuous union of connected machines (or “peers”) communicating with one another and sharing and exploiting common resources.
The flexibility gained for users with both client/server and P2P networks comes with a price, however. It is very difficult to manage diverse and geographically-disparate networks. Machines installed in a typical wide area network are frequently not all of the same variety. One office of a given enterprise may be using IBM personal computers with UNIX operating systems, another office may employ Sun Microsystems workstations with LINUX operating systems, and a third office may employ Hewlett-Packard personal computers running Microsoft Windows® XP. Also, applications present on the machines throughout the network vary not only in terms of type, but also product release level within an application type. Moreover, the applications available are changed frequently by individual users throughout the network, and failure events in such a network are usually difficult to catch until after a failure has already occurred.
One class of network management systems has been implemented according to the well-known Simple Network Management Protocol (“SNMP”) as described, for example, in Marshall T. Rose, The Simple Book (2d ed., PTR Prentice-Hall, Inc., 1994). The SNMP protocol specifies that only one “agent” will exist on a given managed client in a network regardless of the number of server processes interested in monitoring the resources associated with the client. The SNMP protocol is designed such that a set of information called a Management Information Base (“MIB”) will be locally available in storage for each such agent in the network. The MIB acts to define the objects, or resources, that can be monitored using the SNMP protocol. In operation, an SNMP agent will monitor objects associated with its client in accordance with the information comprising the MIB independently of the existence of a server process interested in the objects. However, an SNMP system is inefficient and inflexible in that a server must request information from the agent about objects on a piecemeal basis, one request per piece of information, causing increased network traffic, overhead in the computer system running the console and latency in detecting abnormal conditions. In addition, SNMP does not work properly over P2P networks, as there are no servers on P2P networks to direct the clients as to which data to record. Finally, SNMP agents are relatively simple, and serve to merely store information about the system without actively analyzing or modifying the particular client upon which the information is stored.
Other enterprise management systems available in the prior art operate primarily on client/server networks. Like SNMP, these systems typically require the existence of servers or managers to direct the individual clients as to what information to track or store. Clients themselves have little autonomy. In addition, the information is typically recorded in a mere log file, and is not easily searchable or comparable by the client against information recorded previously. In addition, real-time analysis is nearly impossible for these systems. A network manager typically must wait until data is compiled before making changes to individual clients on the network. Moreover, clients do not have the autonomy to change themselves in response to any actions or events that they may be experiencing. Thus, users experiencing problems on individual clients often have to wait until administrators or managing servers were available in order to solve said problems. As information technology departments are often understaffed, the time a given user might have to wait until his or her problems are resolved could be significant, often amounting to hours or days.